Introduction
Materials and methods
Results and discussion
3.1. Exploratory data analysis
3.2. Modeling
Conclusion
May 10, 2021
Introduction
Materials and methods
Results and discussion
3.1. Exploratory data analysis
3.2. Modeling
Conclusion
PATIENTS.CSV: Contains information about the individuals that received the vaccines
## # A tibble: 34,121 x 35 ## VAERS_ID RECVDATE STATE AGE_YRS CAGE_YR CAGE_MO SEX RPT_DATE SYMPTOM_TEXT ## <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr> <date> <chr> ## 1 0916600 01/01/20… TX 33 33 NA F NA "Right side… ## 2 0916601 01/01/20… CA 73 73 NA F NA "Approximat… ## 3 0916602 01/01/20… WA 23 23 NA F NA "About 15 m… ## # … with 34,118 more rows, and 26 more variables: DIED <chr>, DATEDIED <chr>, ## # L_THREAT <chr>, ER_VISIT <chr>, HOSPITAL <chr>, HOSPDAYS <dbl>, ## # X_STAY <chr>, DISABLE <chr>, RECOVD <chr>, VAX_DATE <chr>, ## # ONSET_DATE <chr>, NUMDAYS <dbl>, LAB_DATA <chr>, V_ADMINBY <chr>, ## # V_FUNDBY <chr>, OTHER_MEDS <chr>, CUR_ILL <chr>, HISTORY <chr>, ## # PRIOR_VAX <chr>, SPLTTYPE <chr>, FORM_VERS <dbl>, TODAYS_DATE <chr>, ## # BIRTH_DEFECT <chr>, OFC_VISIT <chr>, ER_ED_VISIT <chr>, ALLERGIES <chr>
VACCINES.CSV: Contains information about the received vaccine
## # A tibble: 34,630 x 8 ## VAERS_ID VAX_TYPE VAX_MANU VAX_LOT VAX_DOSE_SERIES VAX_ROUTE VAX_SITE ## <chr> <chr> <chr> <chr> <chr> <chr> <chr> ## 1 0916600 COVID19 "MODERNA" 037K20A 1 IM LA ## 2 0916601 COVID19 "MODERNA" 025L20A 1 IM RA ## 3 0916602 COVID19 "PFIZER\\BIONTE… EL1284 1 IM LA ## 4 0916603 COVID19 "MODERNA" unknown <NA> <NA> <NA> ## 5 0916604 COVID19 "MODERNA" <NA> 1 IM LA ## 6 0916606 COVID19 "MODERNA" 011J20A 1 IM LA ## 7 0916607 COVID19 "MODERNA" <NA> <NA> IM LA ## 8 0916608 COVID19 "MODERNA" <NA> 1 IM LA ## 9 0916609 COVID19 "MODERNA" 011J20… 1 IM LA ## 10 0916610 COVID19 "MODERNA" <NA> 1 SYR LA ## # … with 34,620 more rows, and 1 more variable: VAX_NAME <chr>
SYMPTOMS.CSV: Contains information about the symptoms experienced after vaccination
## # A tibble: 48,110 x 11 ## VAERS_ID SYMPTOM1 SYMPTOMVERSION1 SYMPTOM2 SYMPTOMVERSION2 SYMPTOM3 ## <chr> <chr> <dbl> <chr> <dbl> <chr> ## 1 0916600 Dysphagia 23.1 Epiglottitis 23.1 <NA> ## 2 0916601 Anxiety 23.1 Dyspnoea 23.1 <NA> ## 3 0916602 Chest disco… 23.1 Dysphagia 23.1 Pain in ex… ## 4 0916603 Dizziness 23.1 Fatigue 23.1 Mobility d… ## 5 0916604 Injection s… 23.1 Injection s… 23.1 Injection … ## 6 0916606 Pharyngeal … 23.1 <NA> NA <NA> ## # … with 48,104 more rows, and 5 more variables: SYMPTOMVERSION3 <dbl>, ## # SYMPTOM4 <chr>, SYMPTOMVERSION4 <dbl>, SYMPTOM5 <chr>, ## # SYMPTOMVERSION5 <dbl>
The aim of this project is to gain insight on the adverse effects of different Covid-19 vaccines and answer questions such as:
Do some vaccines cause more/different symptoms than others?
Do patients with some profiles get more/different symptoms?
Are certain symptoms correlated with death?
Is patient profile correlated with death?
Does taking anti-inflammatory drugs reduce the chance of having symptoms?
## # A tibble: 3 x 3 ## VAERS_ID OTHER_MEDS TAKES_ANTIINFLAMATORY ## <chr> <chr> <chr> ## 1 0916983 <NA> N ## 2 0916988 Ibuprofen PM the night before Y ## 3 0916996 Clobetasol, Benadryl N
## # A tibble: 3 x 2 ## SEX n ## <chr> <int> ## 1 F 24070 ## 2 M 8514 ## 3 <NA> 828
## # A tibble: 3 x 2 ## VAX_MANU n ## <chr> <int> ## 1 JANSSEN 1106 ## 2 MODERNA 16253 ## 3 PFIZER-BIONTECH 16053
Hypothesis: two peaks corresponding to the innate and acquired immune response. Stronger innate response in younger individuals.
Observations: no noticeable differences
Observations: no noticeable differences
Hypothesis: symptoms associated to a strong immune response are most common in younger groups.
Observations: some noticeable differences, hereamongst death, more common in males.
Observations: Janssen causes the most common symptoms more often (n.b. smaller sample size)
Observations: no observable clustering.
glm(death ~ sex + age + allergic/not + ill/not + has/had covid/not, family = binomial)
Observations: Age, illness and being male are positively correlated with death (p-value < 0.05).
glm(death ~ symptoms, family = binomial)
Observations: asthenia, dyspnoea and vomiting are positively correlated with death (p-value < 0.05).
glm(each symptom ~ takes anti-inflammatory/not , family = binomial)
Observations: no significant reduction in symptoms (p-value < 0.05). Possible increase?
## # A tibble: 2 x 4 ## DIED JANSSEN MODERNA `PFIZER-BIONTECH` ## <chr> <dbl> <dbl> <dbl> ## 1 N 1090 15281 15212 ## 2 Y 16 972 841
Observations: there is a significant difference among vaccine types (p-value < 0.05).
## # A tibble: 2 x 3 ## DIED F M ## <chr> <dbl> <dbl> ## 1 N 23271 7523 ## 2 Y 799 991
Observations: death is significantly more common in males (p-value < 0.05).
Uneven group sizes difficults interpretation of results. Knowing this, we observed the following:
Most vaccine recipients experience symptoms immediately.
Symptoms associated to the expected immune response happen more often in younger age groups.
Age, illness and being male are positively correlated with death.
Asthenia, dyspnoea and vomiting are positively correlated with death.
Anti-inflammatory drugs do not reduce symptoms.
The proportion of death varies among vaccine types.
The proportion of death is higher in males.
Dataset: https://www.kaggle.com/ayushggarg/covid19-vaccine-adverse-reactions?select=2021VAERSSYMPTOMS.csv
Dataset user guide: https://vaers.hhs.gov/docs/VAERSDataUseGuide_November2020.pdf